New Costumer list Report

Dataset statistics

Number of variables	18
Number of observations	1000
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	698.2 KiB
Average record size in memory	714.9 B

Variable types

CAT	9
NUM	8
BOOL	1

Reproduction

Analysis started	2020-06-18 15:28:39.351939
Analysis finished	2020-06-18 15:28:47.034468
Duration	7.68 seconds
Version	pandas-profiling v2.8.0
Command line	`pandas_profiling --config_file config.yaml [YOUR_FILE.csv]`
Download configuration	config.yaml

Warnings

`deceased_indicator` has constant value "N"	Constant
`country` has constant value "Australia"	Constant
`first_name` has a high cardinality: 940 distinct values	High cardinality
`last_name` has a high cardinality: 961 distinct values	High cardinality
`Age` is highly correlated with `DOB`	High correlation
`DOB` is highly correlated with `Age`	High correlation
`Value` is highly correlated with `Rank`	High correlation
`Rank` is highly correlated with `Value`	High correlation
`first_name` is uniformly distributed	Uniform
`last_name` is uniformly distributed	Uniform
`address` has unique values	Unique

first_name
Categorical

HIGH CARDINALITY
UNIFORM

Distinct count	940
Unique (%)	94.0%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Mandie	3
Rozamond	3
Dorian	3
Cissiee	2
Sada	2
Other values (935)	987

Value	Count	Frequency (%)
Mandie	3	0.3%
Rozamond	3	0.3%
Dorian	3	0.3%
Cissiee	2	0.2%
Sada	2	0.2%
Renie	2	0.2%
Cami	2	0.2%
Marcelia	2	0.2%
Cristen	2	0.2%
Tanya	2	0.2%
Nicol	2	0.2%
Tannie	2	0.2%
Jesse	2	0.2%
Dmitri	2	0.2%
Deirdre	2	0.2%
Daisy	2	0.2%
Anthony	2	0.2%
Corinna	2	0.2%
Latrena	2	0.2%
Harman	2	0.2%
Wheeler	2	0.2%
Muffin	2	0.2%
Geoff	2	0.2%
Leticia	2	0.2%
Farlie	2	0.2%
Other values (915)	947	94.7%

Length

Max length	13
Median length	6
Mean length	6.087
Min length	2

Overview of Unicode Properties

Unique unicode characters	52
Unique unicode categories (?)	3
Unique unicode scripts (?)	2
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
e	702	11.5%
a	631	10.4%
i	566	9.3%
n	488	8.0%
r	434	7.1%
l	414	6.8%
o	303	5.0%
t	223	3.7%
d	193	3.2%
y	168	2.8%
s	168	2.8%
h	140	2.3%
u	108	1.8%
c	99	1.6%
m	92	1.5%
A	88	1.4%
C	80	1.3%
M	75	1.2%
b	74	1.2%
D	71	1.2%
g	71	1.2%
S	64	1.1%
R	63	1.0%
L	61	1.0%
B	56	0.9%
Other values (27)	655	10.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	5086	83.6%
Uppercase Letter	1000	16.4%
Dash Punctuation	1	< 0.1%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
A	88	8.8%
C	80	8.0%
M	75	7.5%
D	71	7.1%
S	64	6.4%
R	63	6.3%
L	61	6.1%
B	56	5.6%
K	54	5.4%
G	54	5.4%
T	43	4.3%
J	42	4.2%
E	41	4.1%
F	33	3.3%
H	33	3.3%
N	30	3.0%
P	29	2.9%
W	23	2.3%
O	17	1.7%
I	15	1.5%
V	13	1.3%
Z	7	0.7%
Y	4	0.4%
Q	3	0.3%
X	1	0.1%

Most frequent Lowercase Letter characters

Value	Count	Frequency (%)
e	702	13.8%
a	631	12.4%
i	566	11.1%
n	488	9.6%
r	434	8.5%
l	414	8.1%
o	303	6.0%
t	223	4.4%
d	193	3.8%
y	168	3.3%
s	168	3.3%
h	140	2.8%
u	108	2.1%
c	99	1.9%
m	92	1.8%
b	74	1.5%
g	71	1.4%
k	55	1.1%
v	39	0.8%
p	31	0.6%
f	27	0.5%
w	24	0.5%
z	19	0.4%
x	11	0.2%
q	4	0.1%

Most frequent Dash Punctuation characters

Value	Count	Frequency (%)
-	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	6086	> 99.9%
Common	1	< 0.1%

Most frequent Latin characters

Value	Count	Frequency (%)
e	702	11.5%
a	631	10.4%
i	566	9.3%
n	488	8.0%
r	434	7.1%
l	414	6.8%
o	303	5.0%
t	223	3.7%
d	193	3.2%
y	168	2.8%
s	168	2.8%
h	140	2.3%
u	108	1.8%
c	99	1.6%
m	92	1.5%
A	88	1.4%
C	80	1.3%
M	75	1.2%
b	74	1.2%
D	71	1.2%
g	71	1.2%
S	64	1.1%
R	63	1.0%
L	61	1.0%
B	56	0.9%
Other values (26)	654	10.7%

Most frequent Common characters

Value	Count	Frequency (%)
-	1	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6087	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
e	702	11.5%
a	631	10.4%
i	566	9.3%
n	488	8.0%
r	434	7.1%
l	414	6.8%
o	303	5.0%
t	223	3.7%
d	193	3.2%
y	168	2.8%
s	168	2.8%
h	140	2.3%
u	108	1.8%
c	99	1.6%
m	92	1.5%
A	88	1.4%
C	80	1.3%
M	75	1.2%
b	74	1.2%
D	71	1.2%
g	71	1.2%
S	64	1.1%
R	63	1.0%
L	61	1.0%
B	56	0.9%
Other values (27)	655	10.8%

last_name
Categorical

HIGH CARDINALITY
UNIFORM

Distinct count	961
Unique (%)	96.1%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Van den Velde	3
Burgoine	3
Larose	2
Brettelle	2
Lavalde	2
Other values (956)	988

Value	Count	Frequency (%)
Van den Velde	3	0.3%
Burgoine	3	0.3%
Larose	2	0.2%
Brettelle	2	0.2%
Lavalde	2	0.2%
Hatt	2	0.2%
Fanstone	2	0.2%
Aisthorpe	2	0.2%
Rouchy	2	0.2%
Giffin	2	0.2%
Minshall	2	0.2%
Perkins	2	0.2%
Dobbs	2	0.2%
Poolton	2	0.2%
Goodyear	2	0.2%
Eliet	2	0.2%
Headon	2	0.2%
Trethewey	2	0.2%
Costi	2	0.2%
Sturch	2	0.2%
Brookz	2	0.2%
Shoesmith	2	0.2%
Hallt	2	0.2%
Winward	2	0.2%
Yearsley	2	0.2%
Other values (936)	948	94.8%

Length

Max length	21
Median length	7
Mean length	7.022
Min length	3

Overview of Unicode Properties

Unique unicode characters	54
Unique unicode categories (?)	5
Unique unicode scripts (?)	2
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
e	729	10.4%
a	542	7.7%
n	515	7.3%
r	467	6.7%
o	460	6.6%
l	421	6.0%
i	419	6.0%
t	373	5.3%
s	325	4.6%
d	213	3.0%
c	183	2.6%
h	183	2.6%
u	164	2.3%
y	159	2.3%
m	148	2.1%
B	124	1.8%
k	112	1.6%
g	112	1.6%
b	100	1.4%
w	95	1.4%
S	94	1.3%
C	94	1.3%
M	80	1.1%
p	71	1.0%
D	69	1.0%
Other values (29)	770	11.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	5950	84.7%
Uppercase Letter	1044	14.9%
Space Separator	17	0.2%
Other Punctuation	10	0.1%
Dash Punctuation	1	< 0.1%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
B	124	11.9%
S	94	9.0%
C	94	9.0%
M	80	7.7%
D	69	6.6%
P	61	5.8%
H	58	5.6%
A	52	5.0%
G	51	4.9%
R	44	4.2%
W	40	3.8%
L	40	3.8%
F	39	3.7%
T	35	3.4%
K	33	3.2%
E	32	3.1%
O	26	2.5%
V	22	2.1%
J	15	1.4%
N	14	1.3%
I	9	0.9%
Y	6	0.6%
U	3	0.3%
Q	2	0.2%
Z	1	0.1%

Most frequent Lowercase Letter characters

Value	Count	Frequency (%)
e	729	12.3%
a	542	9.1%
n	515	8.7%
r	467	7.8%
o	460	7.7%
l	421	7.1%
i	419	7.0%
t	373	6.3%
s	325	5.5%
d	213	3.6%
c	183	3.1%
h	183	3.1%
u	164	2.8%
y	159	2.7%
m	148	2.5%
k	112	1.9%
g	112	1.9%
b	100	1.7%
w	95	1.6%
p	71	1.2%
v	58	1.0%
f	49	0.8%
z	39	0.7%
x	10	0.2%
j	2	< 0.1%

Most frequent Space Separator characters

Value	Count	Frequency (%)
	17	100.0%

Most frequent Other Punctuation characters

Value	Count	Frequency (%)
'	10	100.0%

Most frequent Dash Punctuation characters

Value	Count	Frequency (%)
-	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	6994	99.6%
Common	28	0.4%

Most frequent Latin characters

Value	Count	Frequency (%)
e	729	10.4%
a	542	7.7%
n	515	7.4%
r	467	6.7%
o	460	6.6%
l	421	6.0%
i	419	6.0%
t	373	5.3%
s	325	4.6%
d	213	3.0%
c	183	2.6%
h	183	2.6%
u	164	2.3%
y	159	2.3%
m	148	2.1%
B	124	1.8%
k	112	1.6%
g	112	1.6%
b	100	1.4%
w	95	1.4%
S	94	1.3%
C	94	1.3%
M	80	1.1%
p	71	1.0%
D	69	1.0%
Other values (26)	742	10.6%

Most frequent Common characters

Value	Count	Frequency (%)
	17	60.7%
'	10	35.7%
-	1	3.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	7022	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
e	729	10.4%
a	542	7.7%
n	515	7.3%
r	467	6.7%
o	460	6.6%
l	421	6.0%
i	419	6.0%
t	373	5.3%
s	325	4.6%
d	213	3.0%
c	183	2.6%
h	183	2.6%
u	164	2.3%
y	159	2.3%
m	148	2.1%
B	124	1.8%
k	112	1.6%
g	112	1.6%
b	100	1.4%
w	95	1.4%
S	94	1.3%
C	94	1.3%
M	80	1.1%
p	71	1.0%
D	69	1.0%
Other values (29)	770	11.0%

gender
Categorical

Distinct count	3
Unique (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Female	513
Male	470
U	17

Value	Count	Frequency (%)
Female	513	51.3%
Male	470	47.0%
U	17	1.7%

Length

Max length	6
Median length	6
Mean length	4.975
Min length	1

Overview of Unicode Properties

Unique unicode characters	7
Unique unicode categories (?)	2
Unique unicode scripts (?)	1
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
e	1496	30.1%
a	983	19.8%
l	983	19.8%
F	513	10.3%
m	513	10.3%
M	470	9.4%
U	17	0.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3975	79.9%
Uppercase Letter	1000	20.1%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
F	513	51.3%
M	470	47.0%
U	17	1.7%

Most frequent Lowercase Letter characters

Value	Count	Frequency (%)
e	1496	37.6%
a	983	24.7%
l	983	24.7%
m	513	12.9%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4975	100.0%

Most frequent Latin characters

Value	Count	Frequency (%)
e	1496	30.1%
a	983	19.8%
l	983	19.8%
F	513	10.3%
m	513	10.3%
M	470	9.4%
U	17	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4975	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
e	1496	30.1%
a	983	19.8%
l	983	19.8%
F	513	10.3%
m	513	10.3%
M	470	9.4%
U	17	0.3%

past_3_years_bike_related_purchases
Real number (ℝ_≥0)

Distinct count	100
Unique (%)	10.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	49.836
Minimum	0
Maximum	99
Zeros	9
Zeros (%)	0.9%
Memory size	7.9 KiB

Quantile statistics

Minimum	0
5-th percentile	5
Q1	26.75
median	51
Q3	72
95-th percentile	94
Maximum	99
Range	99
Interquartile range (IQR)	45.25

Descriptive statistics

Standard deviation	27.79668613
Coefficient of variation (CV)	0.5577631858
Kurtosis	-1.088048884
Mean	49.836
Median Absolute Deviation (MAD)	22.5
Skewness	-0.06562186172
Sum	49836
Variance	772.6557598

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
60	20	2.0%
59	18	1.8%
70	17	1.7%
42	17	1.7%
37	16	1.6%
11	16	1.6%
47	15	1.5%
84	14	1.4%
62	14	1.4%
57	14	1.4%
67	14	1.4%
79	14	1.4%
30	13	1.3%
15	13	1.3%
71	13	1.3%
64	13	1.3%
7	13	1.3%
44	13	1.3%
5	13	1.3%
46	12	1.2%
83	12	1.2%
82	12	1.2%
25	12	1.2%
50	12	1.2%
94	12	1.2%
Other values (75)	648	64.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	9	0.9%
1	8	0.8%
2	9	0.9%
3	9	0.9%
4	10	1.0%
5	13	1.3%
6	10	1.0%
7	13	1.3%
8	7	0.7%
9	5	0.5%

Value	Count	Frequency (%)
99	9	0.9%
98	6	0.6%
97	11	1.1%
96	9	0.9%
95	8	0.8%
94	12	1.2%
93	9	0.9%
92	5	0.5%
91	8	0.8%
90	6	0.6%

DOB
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct count	958
Unique (%)	95.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	26060.673
Minimum	14039
Maximum	37314
Zeros	0
Zeros (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	14039
5-th percentile	15560.3
Q1	21106
median	26397
Q3	30526.25
95-th percentile	35952.7
Maximum	37314
Range	23275
Interquartile range (IQR)	9420.25

Descriptive statistics

Standard deviation	6241.119342
Coefficient of variation (CV)	0.2394841968
Kurtosis	-0.9544311444
Mean	26060.673
Median Absolute Deviation (MAD)	5007.5
Skewness	-0.01649317203
Sum	26060673
Variance	38951570.64

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
23248	3	0.3%
27610	2	0.2%
34645	2	0.2%
28789	2	0.2%
34924	2	0.2%
31792	2	0.2%
33843	2	0.2%
23926	2	0.2%
29064	2	0.2%
33890	2	0.2%
19272	2	0.2%
15178	2	0.2%
28437	2	0.2%
36702	2	0.2%
28838	2	0.2%
28505	2	0.2%
25944	2	0.2%
24109	2	0.2%
26797	2	0.2%
34439	2	0.2%
34122	2	0.2%
35726	2	0.2%
18888	2	0.2%
16599	2	0.2%
18748	2	0.2%
Other values (933)	949	94.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
14039	1	0.1%
14040	1	0.1%
14097	1	0.1%
14122	1	0.1%
14123	1	0.1%
14125	1	0.1%
14133	1	0.1%
14169	1	0.1%
14193	1	0.1%
14213	1	0.1%

Value	Count	Frequency (%)
37314	1	0.1%
37273	1	0.1%
37260	1	0.1%
37254	1	0.1%
37181	1	0.1%
37161	1	0.1%
37107	1	0.1%
37063	1	0.1%
36998	1	0.1%
36997	1	0.1%

Age
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct count	958
Unique (%)	95.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	49.151173921867084
Minimum	18.3201410451548
Maximum	82.087264332826
Zeros	0
Zeros (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	18.32014105
5-th percentile	22.04973009
Q1	36.91671639
median	48.22973009
Q3	62.7256205
95-th percentile	77.91931913
Maximum	82.08726433
Range	63.76712329
Interquartile range (IQR)	25.80890411

Descriptive statistics

Standard deviation	17.0989571
Coefficient of variation (CV)	0.3478850195
Kurtosis	-0.9544311444
Mean	49.15117392
Median Absolute Deviation (MAD)	13.71917808
Skewness	0.01649317203
Sum	49151.17392
Variance	292.3743339

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
56.85712735	3	0.3%
25.63246981	2	0.2%
54.9995931	2	0.2%
49.47082598	2	0.2%
69.1886342	2	0.2%
68.60507255	2	0.2%
53.92836022	2	0.2%
24.86808625	2	0.2%
45.51466159	2	0.2%
22.67082598	2	0.2%
64.610552	2	0.2%
49.18315474	2	0.2%
69.18589447	2	0.2%
75.0735657	2	0.2%
27.06534652	2	0.2%
55.35027803	2	0.2%
40.92288077	2	0.2%
29.91466159	2	0.2%
41.54205885	2	0.2%
27.70096296	2	0.2%
42.45438762	2	0.2%
44.90644242	2	0.2%
27.82973009	2	0.2%
67.75027803	2	0.2%
68.80233283	2	0.2%
Other values (933)	949	94.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
18.32014105	1	0.1%
18.43246981	1	0.1%
18.46808625	1	0.1%
18.48452461	1	0.1%
18.68452461	1	0.1%
18.73931913	1	0.1%
18.88726433	1	0.1%
19.00781228	1	0.1%
19.18589447	1	0.1%
19.1886342	1	0.1%

Value	Count	Frequency (%)
82.08726433	1	0.1%
82.08452461	1	0.1%
81.92836022	1	0.1%
81.85986707	1	0.1%
81.85712735	1	0.1%
81.85164789	1	0.1%
81.82973009	1	0.1%
81.73109995	1	0.1%
81.66534652	1	0.1%
81.610552	1	0.1%

job_industry_category
Categorical

Distinct count	9
Unique (%)	0.9%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Manufacturing	246
Financial Services	239
Health	171
Retail	101
Property	78
Other values (4)	165

Value	Count	Frequency (%)
Manufacturing	246	24.6%
Financial Services	239	23.9%
Health	171	17.1%
Retail	101	10.1%
Property	78	7.8%
IT	60	6.0%
Entertainment	39	3.9%
Telecommunications	34	3.4%
Argiculture	32	3.2%

Length

Max length	18
Median length	13
Mean length	11.347
Min length	2

Overview of Unicode Properties

Unique unicode characters	29
Unique unicode categories (?)	3
Unique unicode scripts (?)	2
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
a	1315	11.6%
i	1203	10.6%
n	1155	10.2%
e	1006	8.9%
c	824	7.3%
t	779	6.9%
r	744	6.6%
u	590	5.2%
l	577	5.1%
g	278	2.4%
s	273	2.4%
M	246	2.2%
f	246	2.2%
F	239	2.1%
	239	2.1%
S	239	2.1%
v	239	2.1%
H	171	1.5%
h	171	1.5%
o	146	1.3%
m	107	0.9%
R	101	0.9%
T	94	0.8%
P	78	0.7%
p	78	0.7%
Other values (4)	209	1.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	9809	86.4%
Uppercase Letter	1299	11.4%
Space Separator	239	2.1%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
M	246	18.9%
F	239	18.4%
S	239	18.4%
H	171	13.2%
R	101	7.8%
T	94	7.2%
P	78	6.0%
I	60	4.6%
E	39	3.0%
A	32	2.5%

Most frequent Lowercase Letter characters

Value	Count	Frequency (%)
a	1315	13.4%
i	1203	12.3%
n	1155	11.8%
e	1006	10.3%
c	824	8.4%
t	779	7.9%
r	744	7.6%
u	590	6.0%
l	577	5.9%
g	278	2.8%
s	273	2.8%
f	246	2.5%
v	239	2.4%
h	171	1.7%
o	146	1.5%
m	107	1.1%
p	78	0.8%
y	78	0.8%

Most frequent Space Separator characters

Value	Count	Frequency (%)
	239	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	11108	97.9%
Common	239	2.1%

Most frequent Latin characters

Value	Count	Frequency (%)
a	1315	11.8%
i	1203	10.8%
n	1155	10.4%
e	1006	9.1%
c	824	7.4%
t	779	7.0%
r	744	6.7%
u	590	5.3%
l	577	5.2%
g	278	2.5%
s	273	2.5%
M	246	2.2%
f	246	2.2%
F	239	2.2%
S	239	2.2%
v	239	2.2%
H	171	1.5%
h	171	1.5%
o	146	1.3%
m	107	1.0%
R	101	0.9%
T	94	0.8%
P	78	0.7%
p	78	0.7%
y	78	0.7%
Other values (3)	131	1.2%

Most frequent Common characters

Value	Count	Frequency (%)
	239	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11347	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
a	1315	11.6%
i	1203	10.6%
n	1155	10.2%
e	1006	8.9%
c	824	7.3%
t	779	6.9%
r	744	6.6%
u	590	5.2%
l	577	5.1%
g	278	2.4%
s	273	2.4%
M	246	2.2%
f	246	2.2%
F	239	2.1%
	239	2.1%
S	239	2.1%
v	239	2.1%
H	171	1.5%
h	171	1.5%
o	146	1.3%
m	107	0.9%
R	101	0.9%
T	94	0.8%
P	78	0.7%
p	78	0.7%
Other values (4)	209	1.8%

wealth_segment
Categorical

Distinct count	3
Unique (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Mass Customer	508
High Net Worth	251
Affluent Customer	241

Value	Count	Frequency (%)
Mass Customer	508	50.8%
High Net Worth	251	25.1%
Affluent Customer	241	24.1%

Length

Max length	17
Median length	13
Mean length	14.215
Min length	13

Overview of Unicode Properties

Unique unicode characters	21
Unique unicode categories (?)	3
Unique unicode scripts (?)	2
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
s	1765	12.4%
t	1492	10.5%
	1251	8.8%
e	1241	8.7%
o	1000	7.0%
r	1000	7.0%
u	990	7.0%
C	749	5.3%
m	749	5.3%
M	508	3.6%
a	508	3.6%
h	502	3.5%
f	482	3.4%
H	251	1.8%
i	251	1.8%
g	251	1.8%
N	251	1.8%
W	251	1.8%
A	241	1.7%
l	241	1.7%
n	241	1.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	10713	75.4%
Uppercase Letter	2251	15.8%
Space Separator	1251	8.8%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
C	749	33.3%
M	508	22.6%
H	251	11.2%
N	251	11.2%
W	251	11.2%
A	241	10.7%

Most frequent Lowercase Letter characters

Value	Count	Frequency (%)
s	1765	16.5%
t	1492	13.9%
e	1241	11.6%
o	1000	9.3%
r	1000	9.3%
u	990	9.2%
m	749	7.0%
a	508	4.7%
h	502	4.7%
f	482	4.5%
i	251	2.3%
g	251	2.3%
l	241	2.2%
n	241	2.2%

Most frequent Space Separator characters

Value	Count	Frequency (%)
	1251	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	12964	91.2%
Common	1251	8.8%

Most frequent Latin characters

Value	Count	Frequency (%)
s	1765	13.6%
t	1492	11.5%
e	1241	9.6%
o	1000	7.7%
r	1000	7.7%
u	990	7.6%
C	749	5.8%
m	749	5.8%
M	508	3.9%
a	508	3.9%
h	502	3.9%
f	482	3.7%
H	251	1.9%
i	251	1.9%
g	251	1.9%
N	251	1.9%
W	251	1.9%
A	241	1.9%
l	241	1.9%
n	241	1.9%

Most frequent Common characters

Value	Count	Frequency (%)
	1251	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	14215	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
s	1765	12.4%
t	1492	10.5%
	1251	8.8%
e	1241	8.7%
o	1000	7.0%
r	1000	7.0%
u	990	7.0%
C	749	5.3%
m	749	5.3%
M	508	3.6%
a	508	3.6%
h	502	3.5%
f	482	3.4%
H	251	1.8%
i	251	1.8%
g	251	1.8%
N	251	1.8%
W	251	1.8%
A	241	1.7%
l	241	1.7%
n	241	1.7%

deceased_indicator
Categorical

CONSTANT
REJECTED

Distinct count	1
Unique (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

N	1000

Value	Count	Frequency (%)
N	1000	100.0%

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Overview of Unicode Properties

Unique unicode characters	1
Unique unicode categories (?)	1
Unique unicode scripts (?)	1
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
N	1000	100.0%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1000	100.0%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
N	1000	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1000	100.0%

Most frequent Latin characters

Value	Count	Frequency (%)
N	1000	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1000	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
N	1000	100.0%

owns_car
Boolean

Distinct count	2
Unique (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

No	507
Yes	493

Frequency Table

Value	Count	Frequency (%)
No	507	50.7%
Yes	493	49.3%

tenure
Real number (ℝ_≥0)

Distinct count	23
Unique (%)	2.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	11.388
Minimum	0
Maximum	22
Zeros	2
Zeros (%)	0.2%
Memory size	7.9 KiB

Quantile statistics

Minimum	0
5-th percentile	3
Q1	7
median	11
Q3	15
95-th percentile	20
Maximum	22
Range	22
Interquartile range (IQR)	8

Descriptive statistics

Standard deviation	5.037144908
Coefficient of variation (CV)	0.442320417
Kurtosis	-0.8128152156
Mean	11.388
Median Absolute Deviation (MAD)	4
Skewness	0.07089079797
Sum	11388
Variance	25.37282883

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
9	79	7.9%
13	74	7.4%
11	68	6.8%
10	63	6.3%
12	61	6.1%
7	60	6.0%
5	60	6.0%
17	59	5.9%
15	58	5.8%
8	55	5.5%
14	54	5.4%
16	49	4.9%
6	45	4.5%
18	36	3.6%
4	36	3.6%
19	34	3.4%
3	26	2.6%
21	24	2.4%
20	22	2.2%
2	15	1.5%
22	12	1.2%
1	8	0.8%
0	2	0.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	2	0.2%
1	8	0.8%
2	15	1.5%
3	26	2.6%
4	36	3.6%
5	60	6.0%
6	45	4.5%
7	60	6.0%
8	55	5.5%
9	79	7.9%

Value	Count	Frequency (%)
22	12	1.2%
21	24	2.4%
20	22	2.2%
19	34	3.4%
18	36	3.6%
17	59	5.9%
16	49	4.9%
15	58	5.8%
14	54	5.4%
13	74	7.4%

address
Categorical

UNIQUE

Distinct count	1000
Unique (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

415 Rockefeller Trail	1
79 Manufacturers Plaza	1
33652 Lyons Alley	1
6 Meadow Ridge Pass	1
4 Randy Street	1
Other values (995)	995

Value	Count	Frequency (%)
415 Rockefeller Trail	1	0.1%
79 Manufacturers Plaza	1	0.1%
33652 Lyons Alley	1	0.1%
6 Meadow Ridge Pass	1	0.1%
4 Randy Street	1	0.1%
344 Darwin Junction	1	0.1%
4 Arapahoe Terrace	1	0.1%
8491 Pennsylvania Crossing	1	0.1%
2978 Mccormick Center	1	0.1%
7 Michigan Hill	1	0.1%
989 Graedel Terrace	1	0.1%
5 Southridge Hill	1	0.1%
58231 Tomscot Plaza	1	0.1%
7 Hazelcrest Place	1	0.1%
656 Fuller Street	1	0.1%
8427 Moulton Place	1	0.1%
7 Elgar Road	1	0.1%
4 Bluestem Pass	1	0.1%
34 Jay Hill	1	0.1%
0627 Golf Center	1	0.1%
544 Pawling Road	1	0.1%
0 Larry Park	1	0.1%
7 Johnson Hill	1	0.1%
902 Westend Lane	1	0.1%
8 Fieldstone Street	1	0.1%
Other values (975)	975	97.5%

Length

Max length	26
Median length	18
Mean length	17.582
Min length	9

Overview of Unicode Properties

Unique unicode characters	60
Unique unicode categories (?)	4
Unique unicode scripts (?)	2
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
	2108	12.0%
e	1394	7.9%
a	1152	6.6%
r	1072	6.1%
n	884	5.0%
o	787	4.5%
i	748	4.3%
l	732	4.2%
t	645	3.7%
s	469	2.7%
P	337	1.9%
6	330	1.9%
d	318	1.8%
7	317	1.8%
0	315	1.8%
2	305	1.7%
u	303	1.7%
3	300	1.7%
1	294	1.7%
5	293	1.7%
c	287	1.6%
9	279	1.6%
y	277	1.6%
8	273	1.6%
C	272	1.5%
Other values (35)	3091	17.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	10401	59.2%
Decimal Number	2975	16.9%
Space Separator	2108	12.0%
Uppercase Letter	2098	11.9%

Most frequent Decimal Number characters

Value	Count	Frequency (%)
6	330	11.1%
7	317	10.7%
0	315	10.6%
2	305	10.3%
3	300	10.1%
1	294	9.9%
5	293	9.8%
9	279	9.4%
8	273	9.2%
4	269	9.0%

Most frequent Space Separator characters

Value	Count	Frequency (%)
	2108	100.0%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
P	337	16.1%
C	272	13.0%
S	167	8.0%
M	142	6.8%
A	142	6.8%
T	114	5.4%
R	113	5.4%
D	112	5.3%
L	108	5.1%
H	99	4.7%
W	94	4.5%
B	86	4.1%
J	55	2.6%
G	50	2.4%
F	39	1.9%
N	35	1.7%
E	35	1.7%
V	32	1.5%
K	28	1.3%
O	23	1.1%
U	6	0.3%
I	5	0.2%
Q	4	0.2%

Most frequent Lowercase Letter characters

Value	Count	Frequency (%)
e	1394	13.4%
a	1152	11.1%
r	1072	10.3%
n	884	8.5%
o	787	7.6%
i	748	7.2%
l	732	7.0%
t	645	6.2%
s	469	4.5%
d	318	3.1%
u	303	2.9%
c	287	2.8%
y	277	2.7%
g	232	2.2%
k	212	2.0%
h	175	1.7%
v	159	1.5%
w	152	1.5%
m	119	1.1%
f	75	0.7%
p	70	0.7%
z	65	0.6%
b	49	0.5%
x	19	0.2%
j	5	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	12499	71.1%
Common	5083	28.9%

Most frequent Common characters

Value	Count	Frequency (%)
	2108	41.5%
6	330	6.5%
7	317	6.2%
0	315	6.2%
2	305	6.0%
3	300	5.9%
1	294	5.8%
5	293	5.8%
9	279	5.5%
8	273	5.4%
4	269	5.3%

Most frequent Latin characters

Value	Count	Frequency (%)
e	1394	11.2%
a	1152	9.2%
r	1072	8.6%
n	884	7.1%
o	787	6.3%
i	748	6.0%
l	732	5.9%
t	645	5.2%
s	469	3.8%
P	337	2.7%
d	318	2.5%
u	303	2.4%
c	287	2.3%
y	277	2.2%
C	272	2.2%
g	232	1.9%
k	212	1.7%
h	175	1.4%
S	167	1.3%
v	159	1.3%
w	152	1.2%
M	142	1.1%
A	142	1.1%
m	119	1.0%
T	114	0.9%
Other values (24)	1208	9.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	17582	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
	2108	12.0%
e	1394	7.9%
a	1152	6.6%
r	1072	6.1%
n	884	5.0%
o	787	4.5%
i	748	4.3%
l	732	4.2%
t	645	3.7%
s	469	2.7%
P	337	1.9%
6	330	1.9%
d	318	1.8%
7	317	1.8%
0	315	1.8%
2	305	1.7%
u	303	1.7%
3	300	1.7%
1	294	1.7%
5	293	1.7%
c	287	1.6%
9	279	1.6%
y	277	1.6%
8	273	1.6%
C	272	1.5%
Other values (35)	3091	17.6%

postcode
Real number (ℝ_≥0)

Distinct count	522
Unique (%)	52.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	3019.227
Minimum	2000
Maximum	4879
Zeros	0
Zeros (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	2000
5-th percentile	2046
Q1	2209
median	2800
Q3	3845.5
95-th percentile	4508.05
Maximum	4879
Range	2879
Interquartile range (IQR)	1636.5

Descriptive statistics

Standard deviation	848.8957672
Coefficient of variation (CV)	0.2811632803
Kurtosis	-1.142498217
Mean	3019.227
Median Absolute Deviation (MAD)	635.5
Skewness	0.4921079268
Sum	3019227
Variance	720624.0235

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
2232	9	0.9%
2145	9	0.9%
2168	7	0.7%
2750	7	0.7%
3029	7	0.7%
4207	7	0.7%
2148	7	0.7%
3977	7	0.7%
2066	6	0.6%
4350	6	0.6%
3030	6	0.6%
2121	6	0.6%
3163	6	0.6%
2026	6	0.6%
2770	6	0.6%
2170	6	0.6%
2560	6	0.6%
2250	5	0.5%
4500	5	0.5%
2323	5	0.5%
2114	5	0.5%
2230	5	0.5%
3810	5	0.5%
4165	5	0.5%
4556	5	0.5%
Other values (497)	846	84.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2000	1	0.1%
2007	3	0.3%
2009	2	0.2%
2010	4	0.4%
2011	4	0.4%
2015	1	0.1%
2016	2	0.2%
2017	1	0.1%
2019	3	0.3%
2022	1	0.1%

Value	Count	Frequency (%)
4879	1	0.1%
4852	1	0.1%
4818	2	0.2%
4817	2	0.2%
4814	3	0.3%
4744	1	0.1%
4740	2	0.2%
4720	1	0.1%
4717	1	0.1%
4710	1	0.1%

state
Categorical

Distinct count	3
Unique (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

NSW	506
VIC	266
QLD	228

Value	Count	Frequency (%)
NSW	506	50.6%
VIC	266	26.6%
QLD	228	22.8%

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Overview of Unicode Properties

Unique unicode characters	9
Unique unicode categories (?)	1
Unique unicode scripts (?)	1
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
N	506	16.9%
S	506	16.9%
W	506	16.9%
V	266	8.9%
I	266	8.9%
C	266	8.9%
Q	228	7.6%
L	228	7.6%
D	228	7.6%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	3000	100.0%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
N	506	16.9%
S	506	16.9%
W	506	16.9%
V	266	8.9%
I	266	8.9%
C	266	8.9%
Q	228	7.6%
L	228	7.6%
D	228	7.6%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3000	100.0%

Most frequent Latin characters

Value	Count	Frequency (%)
N	506	16.9%
S	506	16.9%
W	506	16.9%
V	266	8.9%
I	266	8.9%
C	266	8.9%
Q	228	7.6%
L	228	7.6%
D	228	7.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3000	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
N	506	16.9%
S	506	16.9%
W	506	16.9%
V	266	8.9%
I	266	8.9%
C	266	8.9%
Q	228	7.6%
L	228	7.6%
D	228	7.6%

country
Categorical

CONSTANT
REJECTED

Distinct count	1
Unique (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Australia	1000

Value	Count	Frequency (%)
Australia	1000	100.0%

Length

Max length	9
Median length	9
Mean length	9
Min length	9

Overview of Unicode Properties

Unique unicode characters	8
Unique unicode categories (?)	2
Unique unicode scripts (?)	1
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
a	2000	22.2%
A	1000	11.1%
u	1000	11.1%
s	1000	11.1%
t	1000	11.1%
r	1000	11.1%
l	1000	11.1%
i	1000	11.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	8000	88.9%
Uppercase Letter	1000	11.1%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
A	1000	100.0%

Most frequent Lowercase Letter characters

Value	Count	Frequency (%)
a	2000	25.0%
u	1000	12.5%
s	1000	12.5%
t	1000	12.5%
r	1000	12.5%
l	1000	12.5%
i	1000	12.5%

Most occurring scripts

Value	Count	Frequency (%)
Latin	9000	100.0%

Most frequent Latin characters

Value	Count	Frequency (%)
a	2000	22.2%
A	1000	11.1%
u	1000	11.1%
s	1000	11.1%
t	1000	11.1%
r	1000	11.1%
l	1000	11.1%
i	1000	11.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	9000	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
a	2000	22.2%
A	1000	11.1%
u	1000	11.1%
s	1000	11.1%
t	1000	11.1%
r	1000	11.1%
l	1000	11.1%
i	1000	11.1%

property_valuation
Real number (ℝ_≥0)

Distinct count	12
Unique (%)	1.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	7.397
Minimum	1
Maximum	12
Zeros	0
Zeros (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	6
median	8
Q3	9
95-th percentile	11
Maximum	12
Range	11
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	2.758804452
Coefficient of variation (CV)	0.3729626134
Kurtosis	-0.3712799928
Mean	7.397
Median Absolute Deviation (MAD)	2
Skewness	-0.5576112079
Sum	7397
Variance	7.611002002

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
9	173	17.3%
8	162	16.2%
7	138	13.8%
10	116	11.6%
6	70	7.0%
11	62	6.2%
5	57	5.7%
4	53	5.3%
3	51	5.1%
12	46	4.6%
2	42	4.2%
1	30	3.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	30	3.0%
2	42	4.2%
3	51	5.1%
4	53	5.3%
5	57	5.7%
6	70	7.0%
7	138	13.8%
8	162	16.2%
9	173	17.3%
10	116	11.6%

Value	Count	Frequency (%)
12	46	4.6%
11	62	6.2%
10	116	11.6%
9	173	17.3%
8	162	16.2%
7	138	13.8%
6	70	7.0%
5	57	5.7%
4	53	5.3%
3	51	5.1%

Rank
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct count	324
Unique (%)	32.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	498.819
Minimum	1
Maximum	1000
Zeros	0
Zeros (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	1
5-th percentile	50
Q1	250
median	500
Q3	750.25
95-th percentile	948.15
Maximum	1000
Range	999
Interquartile range (IQR)	500.25

Descriptive statistics

Standard deviation	288.8109971
Coefficient of variation (CV)	0.5789895675
Kurtosis	-1.200749808
Mean	498.819
Median Absolute Deviation (MAD)	250
Skewness	0.001245859611
Sum	498819
Variance	83411.79203

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
760	13	1.3%
259	12	1.2%
455	9	0.9%
904	9	0.9%
386	9	0.9%
133	9	0.9%
700	8	0.8%
820	8	0.8%
312	8	0.8%
536	8	0.8%
708	7	0.7%
913	7	0.7%
104	7	0.7%
810	7	0.7%
89	7	0.7%
252	7	0.7%
166	7	0.7%
181	7	0.7%
691	7	0.7%
575	7	0.7%
420	7	0.7%
832	6	0.6%
444	6	0.6%
195	6	0.6%
871	6	0.6%
Other values (299)	806	80.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	3	0.3%
4	2	0.2%
6	2	0.2%
8	2	0.2%
10	2	0.2%
12	1	0.1%
13	1	0.1%
14	2	0.2%
16	1	0.1%
17	2	0.2%

Value	Count	Frequency (%)
1000	1	0.1%
997	3	0.3%
996	1	0.1%
994	2	0.2%
993	1	0.1%
988	5	0.5%
987	1	0.1%
985	2	0.2%
983	2	0.2%
979	4	0.4%

Value
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct count	319
Unique (%)	31.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.88171409375
Minimum	0.34
Maximum	1.71875
Zeros	0
Zeros (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	0.34
5-th percentile	0.45655625
Q1	0.64953125
median	0.86
Q3	1.075
95-th percentile	1.40625
Maximum	1.71875
Range	1.37875
Interquartile range (IQR)	0.42546875

Descriptive statistics

Standard deviation	0.293524508
Coefficient of variation (CV)	0.3329021392
Kurtosis	-0.4524719248
Mean	0.8817140937
Median Absolute Deviation (MAD)	0.213125
Skewness	0.4299025249
Sum	881.7140937
Variance	0.08615663677

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0.6375	13	1.3%
1.0625	12	1.2%
0.9	11	1.1%
0.945625	9	0.9%
0.85	9	0.9%
0.5	9	0.9%
1.2375	9	0.9%
0.8925	9	0.9%
0.6875	8	0.8%
0.584375	8	0.8%
1.02	8	0.8%
0.825	8	0.8%
0.91375	7	0.7%
0.690625	7	0.7%
0.499375	7	0.7%
1.073125	7	0.7%
1.2875	7	0.7%
0.796875	7	0.7%
0.5875	7	0.7%
0.68	7	0.7%
1.158125	7	0.7%
1.3125	7	0.7%
1.175	7	0.7%
0.541875	6	0.6%
1.025	6	0.6%
Other values (294)	798	79.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.34	1	0.1%
0.357	3	0.3%
0.374	1	0.1%
0.3825	2	0.2%
0.391	1	0.1%
0.3995	5	0.5%
0.4	1	0.1%
0.408	2	0.2%
0.41	2	0.2%
0.4165	4	0.4%

Value	Count	Frequency (%)
1.71875	3	0.3%
1.703125	2	0.2%
1.671875	2	0.2%
1.65625	2	0.2%
1.640625	2	0.2%
1.625	1	0.1%
1.609375	1	0.1%
1.59375	2	0.2%
1.5625	1	0.1%
1.546875	2	0.2%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Count
Matrix

First rows

	first_name	last_name	gender	past_3_years_bike_related_purchases	DOB	Age	job_industry_category	wealth_segment	deceased_indicator	owns_car	tenure	address	postcode	state	country	property_valuation	Rank	Value
0	Chickie	Brister	Male	86	21013	62.980415	Manufacturing	Mass Customer	N	Yes	14	45 Shopko Center	4500	QLD	Australia	6	1	1.718750
1	Morly	Genery	Male	69	25649	50.279045	Property	Mass Customer	N	No	16	14 Mccormick Park	2113	NSW	Australia	11	1	1.718750
2	Ardelis	Forrester	Female	10	27269	45.840689	Financial Services	Affluent Customer	N	No	10	5 Colorado Crossing	3505	VIC	Australia	5	1	1.718750
3	Lucine	Stutt	Female	64	28883	41.418771	Manufacturing	Affluent Customer	N	Yes	5	207 Annamark Plaza	4814	QLD	Australia	1	4	1.703125
4	Melinda	Hadlee	Female	34	24006	54.780415	Financial Services	Affluent Customer	N	No	19	115 Montana Place	2093	NSW	Australia	9	4	1.703125
5	Druci	Brandli	Female	39	18747	69.188634	Entertainment	High Net Worth	N	Yes	22	89105 Pearson Terrace	4075	QLD	Australia	7	6	1.671875
6	Rutledge	Hallt	Male	23	28039	43.731100	Financial Services	Mass Customer	N	No	8	7 Nevada Crossing	2620	NSW	Australia	7	6	1.671875
7	Nancie	Vian	Female	74	26660	47.509182	Retail	Mass Customer	N	Yes	10	85 Carioca Point	4814	QLD	Australia	5	8	1.656250
8	Duff	Karlowicz	Male	50	26417	48.174936	Manufacturing	Mass Customer	N	Yes	5	717 West Drive	2200	NSW	Australia	10	8	1.656250
9	Barthel	Docket	Male	72	31261	34.903703	IT	Mass Customer	N	Yes	17	80 Scofield Junction	4151	QLD	Australia	5	10	1.640625

Last rows

	first_name	last_name	gender	past_3_years_bike_related_purchases	DOB	Age	job_industry_category	wealth_segment	deceased_indicator	owns_car	tenure	address	postcode	state	country	property_valuation	Rank	Value
990	Jermaine	Bagshawe	Female	60	19858	66.144799	Property	Mass Customer	N	Yes	9	260 Briar Crest Drive	4209	QLD	Australia	6	988	0.3995
991	Bryan	Jachtym	Male	59	27164	46.128360	Manufacturing	Mass Customer	N	Yes	15	56 Moland Crossing	3356	VIC	Australia	3	988	0.3995
992	Renie	Laundon	Female	32	27016	46.533840	Entertainment	Mass Customer	N	Yes	8	1 Shelley Pass	4118	QLD	Australia	3	993	0.3910
993	Weidar	Etheridge	Male	38	21744	60.977675	Financial Services	Mass Customer	N	Yes	6	0535 Jay Point	2422	NSW	Australia	4	994	0.3825
994	Datha	Fishburn	Female	15	33056	29.985894	Retail	Mass Customer	N	No	3	6 Caliangt Way	3079	VIC	Australia	12	994	0.3825
995	Ferdinand	Romanetti	Male	60	21830	60.742059	Financial Services	Affluent Customer	N	No	9	2 Sloan Way	2200	NSW	Australia	7	996	0.3740
996	Burk	Wortley	Male	22	37181	18.684525	Health	Mass Customer	N	No	6	04 Union Crossing	2196	NSW	Australia	10	997	0.3570
997	Melloney	Temby	Female	17	20002	65.750278	Financial Services	Affluent Customer	N	Yes	15	33475 Fair Oaks Junction	4702	QLD	Australia	2	997	0.3570
998	Dickie	Cubbini	Male	30	19345	67.550278	Financial Services	Mass Customer	N	Yes	19	57666 Victoria Way	4215	QLD	Australia	2	997	0.3570
999	Sylas	Duffill	Male	56	20364	64.758497	Property	Mass Customer	N	Yes	14	21875 Grover Drive	2010	NSW	Australia	9	1000	0.3400

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent Uppercase Letter characters

Most frequent Lowercase Letter characters

Most frequent Dash Punctuation characters

Most occurring scripts

Most frequent Latin characters

Most frequent Common characters

Most occurring blocks

Most frequent ASCII characters

Most occurring characters

Most occurring categories

Most frequent Uppercase Letter characters

Most frequent Lowercase Letter characters

Most frequent Space Separator characters

Most frequent Other Punctuation characters

Most frequent Dash Punctuation characters

Most occurring scripts

Most frequent Latin characters

Most frequent Common characters

Most occurring blocks

Most frequent ASCII characters

Most occurring characters

Most occurring categories

Most frequent Uppercase Letter characters

Most frequent Lowercase Letter characters

Most occurring scripts

Most frequent Latin characters

Most occurring blocks

Most frequent ASCII characters

Most occurring characters

Most occurring categories

Most frequent Uppercase Letter characters

Most frequent Lowercase Letter characters

Most frequent Space Separator characters

Most occurring scripts

Most frequent Latin characters

Most frequent Common characters

Most occurring blocks

Most frequent ASCII characters

Most occurring characters

Most occurring categories

Most frequent Uppercase Letter characters

Most frequent Lowercase Letter characters

Most frequent Space Separator characters

Most occurring scripts

Most frequent Latin characters

Most frequent Common characters

Most occurring blocks

Most frequent ASCII characters

Most occurring characters

Most occurring categories

Most frequent Uppercase Letter characters

Most occurring scripts

Most frequent Latin characters

Most occurring blocks

Most frequent ASCII characters

Most occurring characters

Most occurring categories

Most frequent Decimal Number characters

Most frequent Space Separator characters

Most frequent Uppercase Letter characters

Most frequent Lowercase Letter characters

Most occurring scripts

Most frequent Common characters

Most frequent Latin characters

Most occurring blocks

Most frequent ASCII characters

Most occurring characters

Most occurring categories

Most frequent Uppercase Letter characters

Most occurring scripts

Most frequent Latin characters

Most occurring blocks

Most frequent ASCII characters

Most occurring characters

Most occurring categories

Most frequent Uppercase Letter characters